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Machine Learning Fundamentals

You're reading from Machine Learning Fundamentals Use Python and scikit-learn to get up and running with the hottest developments in machine learning

Product type Paperback

Published in Nov 2018

Publisher

ISBN-13 9781789803556

Length 240 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Hyatt Saleh

View More author details

Table of Contents (8) Chapters

Preface

About the Book

1. Introduction to Scikit-Learn FREE CHAPTER

2. Unsupervised Learning: Real-Life Applications

3. Supervised Learning: Key Steps

4. Supervised Learning Algorithms: Predict Annual Income

5. Artificial Neural Networks: Predict Annual Income

6. Building Your Own Program

Appendix

Unsupervised Learning: Real-Life Applications

Learning Objectives

By the end of this chapter, you will be able to:

Describe how clustering works
Import and preprocess a dataset using Pandas and Matplotlib
Explain the difference between the three clustering algorithms
Solve an unsupervised learning data problem using different algorithms
Compare the results of different algorithms to select the one with the best performance

This chapter describes a practical implementation of an unsupervised algorithm to a real-world dataset

The rest of the chapter is locked

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Authors (1)

Hyatt Saleh

Hyatt Saleh

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored Machine Learning Fundamentals, by Packt Publishing.

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